Monologue vs. Dialogue: A Field Experiment of AI-Enabled Telemarketing

Xincheng Ma, Brian Rongqing Han, Dongwon Lee, Junbum Kwon

Research output: Contribution to conferenceConference Paperpeer-review

Abstract

Artificial intelligence has shifted telemarketing from traditional robocalls to interactive AI-enabled IVR systems. Despite theoretical advantages, the actual effectiveness of AI-enabled dialogue versus traditional monologue telemarketing remains unclear. This study addresses this uncertainty with a randomized field experiment involving 90,000 participants to examine two questions: the comparative efficacy of AI-enabled dialogue telemarketing versus monologue telemarketing, and the relative impact of hedonic versus utilitarian attributes on consumer response. Contrary to prevailing industry assumptions, our results demonstrate that traditional monologue telemarketing significantly outperform AI-enabled dialogue telemarketing, registering an 18.43% higher response rate. Furthermore, within dialogue telemarketing, calls emphasizing utilitarian attributes surpass those focusing on hedonic attributes, with a 16.59% increase in response rate. These results not only challenge the expected advantages of AI-enabled interactive telemarketing but also provide a nuanced understanding of the critical role of utilitarian benefits in telemarketing, contributing valuable insights for more effective AI deployment in telemarketing.
Original languageEnglish
Publication statusPublished - Feb 2024
EventICIS 2024 Proceedings -
Duration: 1 Feb 20241 Feb 2024

Conference

ConferenceICIS 2024 Proceedings
Period1/02/241/02/24

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